李维鹏, 张国良, 姚二亮, 徐君, 林志林. 基于场景显著区域的改进闭环检测算法[J]. 机器人, 2017, 39(1): 23-35. DOI: 10.13973/j.cnki.robot.2017.0023
引用本文: 李维鹏, 张国良, 姚二亮, 徐君, 林志林. 基于场景显著区域的改进闭环检测算法[J]. 机器人, 2017, 39(1): 23-35. DOI: 10.13973/j.cnki.robot.2017.0023
LI Weipeng, ZHANG Guoliang, YAO Erliang, XU Jun, LIN Zhilin. An Improved Loop Closure Detection Algorithm Based on Scene Salient Regions[J]. ROBOT, 2017, 39(1): 23-35. DOI: 10.13973/j.cnki.robot.2017.0023
Citation: LI Weipeng, ZHANG Guoliang, YAO Erliang, XU Jun, LIN Zhilin. An Improved Loop Closure Detection Algorithm Based on Scene Salient Regions[J]. ROBOT, 2017, 39(1): 23-35. DOI: 10.13973/j.cnki.robot.2017.0023

基于场景显著区域的改进闭环检测算法

An Improved Loop Closure Detection Algorithm Based on Scene Salient Regions

  • 摘要: 针对闭环路径不一致、闭环视角变化较大的VSLAM(视觉同时定位与地图创建)闭环检测问题,提出了一种基于场景显著区域的改进闭环检测算法.首先设计了基于场景显著区域的闭环检测架构,并构建了相应的闭环全概率模型.其次,提出了融合特征跟踪率与RGB直方图匹配的关键帧选取方法,降低了闭环检测过程的信息冗余.然后,采用基于逆向索引的预匹配场景选取方法,极大地提高了闭环检测的实时性.最后,根据本文的场景显著区域的几何特点给出了显著区域之间的观测几何匹配概率,提高了闭环检测算法对歧义场景的分辨能力.与FAB-MAP 2.0的对比实验表明,在保证较高的闭环准确率的条件下,本文算法能够有效提高对不重合路径闭环以及大视角变化的闭环的召回率,并具有良好的实时性.

     

    Abstract: An improved loop closure detection algorithm based on scene salient regions is proposed for VSLAM (visual simultaneous localization and mapping) loop closures without consistent path and similar camera view. Firstly, a scene salient region based loop closure detection architecture is structured together with its probabilistic model. Then a key frame selecting method which combines feature tracking rate and RGB histogram matching is proposed to reduce the detection information redundancy. Next, a pre-matched scene selecting method based on inverted index is presented, which greatly improves the real-time performance of loop closure detection. Finally, according to the geometric property of the salient region in this paper, a geometric matching probability in observation is introduced to improve the algorithm's ability of distinguishing perceptual aliasing scenes. The comparative experiments show that the proposed algorithm gets a better recall ratio compared with FAB-MAP 2.0 in a condition of high precision and good real-time performance, when facing loop closures without consistent path and similar camera view.

     

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